




"""simple docstring"""


import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
  from PIL import Image

  from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor


@require_tokenizers
@require_vision
class _lowerCamelCase							(	unittest.TestCase		):






   def 			_lowerCAmelCase       (						self  :						Any       )					->		Dict:

         """simple docstring"""
         lowerCAmelCase__     :					List[str]       =			tempfile.mkdtemp()

         # fmt: off
         lowerCAmelCase__     :					Optional[Any]       =			["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing""", """,""", """low""", """lowest"""]
         # fmt: on
         lowerCAmelCase__     :					Dict       =			os.path.join(self.tmpdirname       ,      VOCAB_FILES_NAMES["""vocab_file"""]       )
         with open(self.vocab_file       ,      """w"""       ,      encoding="""utf-8"""       ) as vocab_writer:
               vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]       )       )

         lowerCAmelCase__     :					Dict       =			{
             """do_resize""": True,
             """size""": {"""height""": 18, """width""": 18},
             """do_normalize""": True,
             """image_mean""": [0.5, 0.5, 0.5],
             """image_std""": [0.5, 0.5, 0.5],
         }
         lowerCAmelCase__     :					Union[str, Any]       =			os.path.join(self.tmpdirname       ,      snake_case_       )
         with open(self.image_processor_file       ,      """w"""       ,      encoding="""utf-8"""       ) as fp:
               json.dump(snake_case_       ,      snake_case_       )






   def 			_lowerCAmelCase       (						self  :						int       ,      **UpperCamelCase  :						str       )					->		Optional[int]:

         """simple docstring"""
         return BertTokenizer.from_pretrained(self.tmpdirname       ,      **snake_case_       )






   def 			_lowerCAmelCase       (						self  :						Tuple       ,      **UpperCamelCase  :						Any       )					->		List[Any]:

         """simple docstring"""
         return ViTImageProcessor.from_pretrained(self.tmpdirname       ,      **snake_case_       )






   def 			_lowerCAmelCase       (						self  :						Any       )					->		int:

         """simple docstring"""
         shutil.rmtree(self.tmpdirname       )






   def 			_lowerCAmelCase       (						self  :						List[Any]       )					->		Optional[int]:

         """simple docstring"""
         lowerCAmelCase__     :					Optional[int]       =			[np.random.randint(2_55       ,      size=(3, 30, 4_00)       ,      dtype=np.uinta       )]

         lowerCAmelCase__     :					Optional[Any]       =			[Image.fromarray(np.moveaxis(snake_case_       ,      0       ,      -1       )       ) for x in image_inputs]

         return image_inputs






   def 			_lowerCAmelCase       (						self  :						int       )					->		Optional[int]:

         """simple docstring"""
         lowerCAmelCase__     :					Tuple       =			self.get_tokenizer()
         lowerCAmelCase__     :					Optional[Any]       =			self.get_image_processor()

         lowerCAmelCase__     :					List[Any]       =			VisionTextDualEncoderProcessor(tokenizer=snake_case_       ,      image_processor=snake_case_       )

         processor.save_pretrained(self.tmpdirname       )
         lowerCAmelCase__     :					Optional[Any]       =			VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname       )

         self.assertEqual(processor.tokenizer.get_vocab()       ,      tokenizer.get_vocab()       )
         self.assertIsInstance(processor.tokenizer       ,      (BertTokenizer, BertTokenizerFast)       )

         self.assertEqual(processor.image_processor.to_json_string()       ,      image_processor.to_json_string()       )
         self.assertIsInstance(processor.image_processor       ,      snake_case_       )






   def 			_lowerCAmelCase       (						self  :						Optional[int]       )					->		Optional[Any]:

         """simple docstring"""
         lowerCAmelCase__     :					Dict       =			VisionTextDualEncoderProcessor(
             tokenizer=self.get_tokenizer()       ,      image_processor=self.get_image_processor()       )
         processor.save_pretrained(self.tmpdirname       )

         lowerCAmelCase__     :					int       =			self.get_tokenizer(bos_token="""(BOS)"""       ,      eos_token="""(EOS)"""       )
         lowerCAmelCase__     :					Union[str, Any]       =			self.get_image_processor(do_normalize=snake_case_       ,      padding_value=1.0       )

         lowerCAmelCase__     :					str       =			VisionTextDualEncoderProcessor.from_pretrained(
             self.tmpdirname       ,      bos_token="""(BOS)"""       ,      eos_token="""(EOS)"""       ,      do_normalize=snake_case_       ,      padding_value=1.0       )

         self.assertEqual(processor.tokenizer.get_vocab()       ,      tokenizer_add_kwargs.get_vocab()       )
         self.assertIsInstance(processor.tokenizer       ,      (BertTokenizer, BertTokenizerFast)       )

         self.assertEqual(processor.image_processor.to_json_string()       ,      image_processor_add_kwargs.to_json_string()       )
         self.assertIsInstance(processor.image_processor       ,      snake_case_       )






   def 			_lowerCAmelCase       (						self  :						Optional[int]       )					->		Optional[Any]:

         """simple docstring"""
         lowerCAmelCase__     :					Any       =			self.get_image_processor()
         lowerCAmelCase__     :					List[Any]       =			self.get_tokenizer()

         lowerCAmelCase__     :					Optional[Any]       =			VisionTextDualEncoderProcessor(tokenizer=snake_case_       ,      image_processor=snake_case_       )

         lowerCAmelCase__     :					str       =			self.prepare_image_inputs()

         lowerCAmelCase__     :					str       =			image_processor(snake_case_       ,      return_tensors="""np"""       )
         lowerCAmelCase__     :					List[str]       =			processor(images=snake_case_       ,      return_tensors="""np"""       )

         for key in input_feat_extract.keys():
               self.assertAlmostEqual(input_feat_extract[key].sum()       ,      input_processor[key].sum()       ,      delta=1E-2       )






   def 			_lowerCAmelCase       (						self  :						Union[str, Any]       )					->		Union[str, Any]:

         """simple docstring"""
         lowerCAmelCase__     :					Dict       =			self.get_image_processor()
         lowerCAmelCase__     :					List[str]       =			self.get_tokenizer()

         lowerCAmelCase__     :					int       =			VisionTextDualEncoderProcessor(tokenizer=snake_case_       ,      image_processor=snake_case_       )

         lowerCAmelCase__     :					Any       =			"""lower newer"""

         lowerCAmelCase__     :					Optional[int]       =			processor(text=snake_case_       )

         lowerCAmelCase__     :					Optional[int]       =			tokenizer(snake_case_       )

         for key in encoded_tok.keys():
               self.assertListEqual(encoded_tok[key]       ,      encoded_processor[key]       )






   def 			_lowerCAmelCase       (						self  :						Tuple       )					->		Any:

         """simple docstring"""
         lowerCAmelCase__     :					Union[str, Any]       =			self.get_image_processor()
         lowerCAmelCase__     :					str       =			self.get_tokenizer()

         lowerCAmelCase__     :					Any       =			VisionTextDualEncoderProcessor(tokenizer=snake_case_       ,      image_processor=snake_case_       )

         lowerCAmelCase__     :					Union[str, Any]       =			"""lower newer"""
         lowerCAmelCase__     :					List[Any]       =			self.prepare_image_inputs()

         lowerCAmelCase__     :					Tuple       =			processor(text=snake_case_       ,      images=snake_case_       )

         self.assertListEqual(list(inputs.keys()       )       ,      ["""input_ids""", """token_type_ids""", """attention_mask""", """pixel_values"""]       )

         # test if it raises when no input is passed
         with self.assertRaises(snake_case_       ):
               processor()






   def 			_lowerCAmelCase       (						self  :						Any       )					->		Dict:

         """simple docstring"""
         lowerCAmelCase__     :					Optional[int]       =			self.get_image_processor()
         lowerCAmelCase__     :					List[Any]       =			self.get_tokenizer()

         lowerCAmelCase__     :					Optional[int]       =			VisionTextDualEncoderProcessor(tokenizer=snake_case_       ,      image_processor=snake_case_       )

         lowerCAmelCase__     :					int       =			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

         lowerCAmelCase__     :					List[str]       =			processor.batch_decode(snake_case_       )
         lowerCAmelCase__     :					Union[str, Any]       =			tokenizer.batch_decode(snake_case_       )

         self.assertListEqual(snake_case_       ,      snake_case_       )






   def 			_lowerCAmelCase       (						self  :						List[str]       )					->		Optional[Any]:

         """simple docstring"""
         lowerCAmelCase__     :					List[Any]       =			self.get_image_processor()
         lowerCAmelCase__     :					Any       =			self.get_tokenizer()

         lowerCAmelCase__     :					List[str]       =			VisionTextDualEncoderProcessor(tokenizer=snake_case_       ,      image_processor=snake_case_       )

         lowerCAmelCase__     :					Union[str, Any]       =			"""lower newer"""
         lowerCAmelCase__     :					Union[str, Any]       =			self.prepare_image_inputs()

         lowerCAmelCase__     :					str       =			processor(text=snake_case_       ,      images=snake_case_       )

         self.assertListEqual(list(inputs.keys()       )       ,      processor.model_input_names       )







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase_    :			Any    =	logging.get_logger(__name__)

lowerCamelCase_    :			Dict    =	{
    """facebook/dpr-ctx_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-single-nq-base""": (
        """https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json"""
    ),
    """facebook/dpr-ctx_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-question_encoder-multiset-base""": (
        """https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json"""
    ),
    """facebook/dpr-reader-multiset-base""": (
        """https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json"""
    ),
}

class 							_UpperCamelCase					(       _A	):






			'''simple docstring'''

			__UpperCamelCase   :    Any          =			"""dpr"""

			def __init__(							self			:							str    ,						snake_case_			:							Any=3_0522    ,						snake_case_			:							List[str]=768    ,						snake_case_			:							List[str]=12    ,						snake_case_			:							Union[str, Any]=12    ,						snake_case_			:							Tuple=3072    ,						snake_case_			:							Any="gelu"    ,						snake_case_			:							Optional[Any]=0.1    ,						snake_case_			:							str=0.1    ,						snake_case_			:							Dict=512    ,						snake_case_			:							int=2    ,						snake_case_			:							Union[str, Any]=0.02    ,						snake_case_			:							str=1e-12    ,						snake_case_			:							List[str]=0    ,						snake_case_			:							Any="absolute"    ,						snake_case_			:							int = 0    ,						**snake_case_			:							int    ,						):
							super().__init__(pad_token_id=snake_case_    ,						**snake_case_   )

							UpperCamelCase_:				str						=    vocab_size
							UpperCamelCase_:				Optional[int]						=    hidden_size
							UpperCamelCase_:				int						=    num_hidden_layers
							UpperCamelCase_:				Any						=    num_attention_heads
							UpperCamelCase_:				int						=    hidden_act
							UpperCamelCase_:				Optional[Any]						=    intermediate_size
							UpperCamelCase_:				Tuple						=    hidden_dropout_prob
							UpperCamelCase_:				Tuple						=    attention_probs_dropout_prob
							UpperCamelCase_:				str						=    max_position_embeddings
							UpperCamelCase_:				Any						=    type_vocab_size
							UpperCamelCase_:				Tuple						=    initializer_range
							UpperCamelCase_:				List[Any]						=    layer_norm_eps
							UpperCamelCase_:				Tuple						=    projection_dim
							UpperCamelCase_:				Dict						=    position_embedding_type






